---
title: "AI Agents Are Just Distributed Systems Now"
category: "talks"
date: "2026-07-01"
time: "2:50pm-3:10pm"
track: "AI-Native Enterprises"
room: "Leadership 1"
speakers: ["Salman Munaf"]
sourceLabels: ["Official conference schedule", "Public YouTube metadata"]
scheduleTrack: "AI-Native Enterprises"
scheduleRoom: "Leadership 1"
scheduleLabels: ["AI-Native Enterprises", "Leadership 1", "session", "confirmed"]
---
# AI Agents Are Just Distributed Systems Now

## Conference Context
- Date/time: 2026-07-01 · 2:50pm-3:10pm
- Track/room: AI-Native Enterprises · Leadership 1
- Speaker(s): Salman Munaf
- Session type/status: session · confirmed

- Track: AI-Native Enterprises
- Room: Leadership 1
- Session type: session
- Status: confirmed

## Session Description
AI agents are often described as a new kind of software, but once they move beyond chat and start calling tools, reading data, making decisions, retrying tasks, and coordinating workflows, they begin to look a lot like distributed systems. They have state. They call external services. They depend on APIs. They fail partially. They retry. They time out. They can loop. They can act on stale context. They can produce inconsistent results. And when something goes wrong, teams need logs, traces, permissions, ownership, and rollback paths just like they do with any other production system. This session will give engineers a practical way to reason about AI agents using familiar distributed systems concepts. We will break down the agent loop: planning, tool use, observation, memory, and retries. Then we will map common agent failure modes to engineering patterns teams already know, including timeouts, circuit breakers, idempotency, rate limits, least privilege, observability, and human approval. The goal is to move past the hype and treat agents like real production systems. Attendees will leave with a clear mental model for designing, debugging, and operating agents safely, especially as they become part of customer-facing products, internal developer tools, and business workflows.

## Media Evidence
No related AI Engineer channel video found yet.

## Evidence Graph
This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.

### Media Signals
No linked video, transcript, or slide source has been attached yet.

### Agent Reading Notes
Use these signals to refine the synopsis, topic links, people/company context, and method notes. If a source is a related external video rather than an exact official recording, keep it framed as supporting evidence.

## Transcript Status
No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

## People
- [[salman-munaf]]

## Notes
- Pending transcript synthesis when an official recording or confirmed matching video is available.

## Synthesis
### Synthesized Breakdown
# AI Agents Are Just Distributed Systems Now ## Conference Context - Date/time: 2026-07-01 · 2:50pm-3:10pm - Track/room: AI-Native Enterprises · Leadership 1 - Speaker(s): Salman Munaf - Session type/status: session · confirmed - Track: AI-Native Enterprises - Room: Leadership 1 - Session type: session - Status: confirmed ## Session Description AI agents are often described as a new kind of software, but once they move beyond chat and start calling tools, reading data, making decisions, retrying tasks, and coordinating workflows, they begin to look a lot like distributed systems. They have state. They call external services. They depend on APIs.

### Speaker And Company Context
- [[salman-munaf|Salman Munaf]] — Lead Site Reliability Engineer at [[tiktok|TikTok]].

### Topics Covered
- [[agent-security]]
- [[coding-agents]]

### Derived Links And Source Material

### Novel Concepts / Clever Methods
- No highlighted novel concept has been detected yet.

### Evidence Boundary
This synthesis is based on the official schedule and linked source pages. It should be revisited when exact session recordings or transcript-backed secondary sources are available.